Performance optimization

ABSTRACT

In embodiments, the present invention is directed to methods of aligning an agent&#39;s compensation with an organization&#39;s goals, incentivizing an agent to improve their performance, and managing an agent. In one embodiment, the present invention includes defining a performance metric that relates to a goal of an organization. Performance levels are then defined for the performance metric. The performance levels are associated with performance values that an agent must meet to have their performance classified within a performance level. The method also includes providing a compensation rule that defines which of the performance levels an agent must achieve to change their current compensation. The performance of an agent with respect to the performance metric is then monitored to generate an agent performance, which is compared to the previously established achievement values to determine an agent&#39;s performance level.

CROSS-REFERENCE TO RELATED APPLICATIONS

This patent application claims priority to U.S. Provisional PatentApplication No. 60/763,070, entitled PERFORMANCE MONITORING filed onJan. 27, 2006; U.S. patent application Ser. No. 11/556,003, entitledSHARED CALL CENTER SYSTEM AND METHODS, filed Nov. 2, 2006. The entirecontents of U.S. Provisional Patent Application No. 60/763,070 and U.S.patent application Ser. No. 11/556,003 are hereby incorporated byreference in their entirety as if set forth herein in full. The presentapplication is related to U.S. patent application Ser. No. 11/627,687entitled PERFORMANCE OPTIMIZATION, filed on the same date as the presentapplication, and hereby incorporated by reference in its entirety; andis also related to PCT Patent Application No. PCT/US2007/002209 entitledPERFORMANCE OPTIMIZATION, filed on the same date as the presentapplication, and hereby incorporated by reference in its entirety.

BACKGROUND

Businesses and other organizations must consistently manage theperformance of their employees in order to maximize the employees'contribution to the organization to help the organization achieve itsstrategic goals. It is difficult to establish a system that consistentlyinspires and motivates employees. Motivating and inspiring employees ismore challenging in client services industries because, although theemployees are employed by an organization, they are performing tasks forclients or customers of the organization. This situation creates adisconnect between employees' motivation to improve their performance,and the clients or customers' achievement of strategic goals.

Compensation is sometimes used as a way of motivating employees.However, oftentimes the performance of employees is not adequatelylinked to their compensation, making compensation an ineffectivemotivator. As an example, if decisions about compensation involve toomuch subjectivity, then it will not serve as an effective tool formotivating employees.

There are various approaches that attempt to address performancemanagement and compensation to employees in the marketplace. Forexample, common approaches involve performance reviews, merit increases,incentive plans, and recognition programs that attempt to solve theperformance management and reward issues within organizations. Some ofthese approaches include running reports to determine “after-the-fact”performance at the end of a reporting period. All of these approachesforce managers and supervisors to review data from many sources and totry to subjectively determine agent performance by their own mentalanalysis.

SUMMARY

This summary is intended to generally describe embodiments of thepresent invention, which are described in greater detail below. Itshould be understood that the summary is not intended to limit the scopeof the present invention, or be used to limit the scope of the claimsattached below.

In embodiments, the present invention provides a computer implementedmethod that is useful, generally, for managing an employee, i.e., anagent employed by an organization. The method may have a number ofembodiments, some examples including, but not limited to, methods formanaging an agent, methods for aligning the compensation of an agentwith goals of an organization, and methods of incentivizing an agent toimprove their performance. In one embodiment of the present invention,the method includes defining a performance metric that relates to a goalof an organization. Performance levels are then defined for theperformance metric. The performance levels are associated with anachievement level that an agent's performance with respect to the metricmust meet to have their performance classified within a performancelevel. The achievement levels are based on an agent's experience, i.e.,the more experienced an agent is, the better the agent will be expectedto perform. The method also includes providing a base pay/incentive rulethat defines the consistency of achievement an agent must reach tochange their current base pay or receive extra incentive pay. Theachievement of an agent with respect to the performance metric is thentracked and displayed to an agent to inspire and motivate the agent'sperformance, which is compared to the previously established achievementlevels to determine an agent's performance level.

In other embodiments, the method may include additional steps, such asautomatically applying the compensation rule based on the agent'sperformance to change a compensation of the agent. The change incompensation may be an increase or decrease. In those embodiments, inwhich the change in compensation is an increase, the increase may be inthe form of a bonus (variable pay component) or an increase in a basesalary/wage (base pay component.). In another embodiment, the method mayinclude the additional steps of communicating the compensation rule tothe agent, and providing the agent with access to performanceinformation, which includes the agent performance metrics, theachievement levels and the resulting agent performance level. Thisembodiment provides for incentivizing an agent to improve theirperformance, because they are made aware of the direct relationship oftheir performance to their compensation, and can also monitor theirperformance.

In embodiments, the present invention can be used to compare, in anormalized manner, resulting performance across disparate agent rolesthat may have very different performance metrics and achievement levels.This allows managers and team leaders to compare and make betterdecisions regarding managing performance across an enterprise. In oneembodiment, performance is normalized in an easy to understand matrixthat compares agent performance to compensation levels to determine thevalue of agents' contributions.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a conceptual depiction of a business model for performanceoptimization according to an embodiment of the present invention.

FIG. 2 is a flow diagram illustrating operational characteristics of aprocess, embodying the business model of FIG. 1, for optimizing theperformance of an agent.

FIG. 3 is a network environment in which a software application tosupport the process is implemented in accordance with an embodiment ofthe present invention.

FIG. 4 illustrates a logical representation of the performanceoptimization software application shown in the network environment ofFIG. 3 in accordance with an embodiment of the present invention.

FIG. 5 depicts a computing system upon which embodiments of the presentinvention may be implemented.

FIG. 6 is a flow diagram illustrating operational characteristics of amethod for monitoring performance using the performance optimizationsoftware application shown in FIGS. 3 and 4 in accordance with anembodiment of the present invention.

FIG. 7 is a flow diagram illustrating operational characteristicsperformed by the performance optimization software application shown inFIGS. 3 and 4 to render display of interfaces to users of the softwareapplication in accordance with an embodiment of the present invention.

FIG. 8 generally illustrates in block diagram format an embodiment of asystem that implements the business model shown in FIG. 1 and thesoftware application shown in FIGS. 3 and 4.

FIG. 9 is a flow diagram illustrating operational characteristics of aprocess for collecting data, calculating achievement and adjustingcompensation in accordance with an embodiment of the present invention.

DETAILED DESCRIPTION

The present invention and its various embodiments are described indetail below with reference to the figures. When referring to thesefigures, like structures and elements shown throughout are indicatedwith like reference numerals. Software components, which may includeroutines, constructs and any other form of source or binary code orvisual elements rendered there from, are logically and generallydepicted in the figures using dashed lines.

In general, the present invention is directed, in embodiments, tooptimize performance of employees, contractors and other agents employedto perform tasks on behalf of a company, business organization or otherentity. In an embodiment, the present invention involves an approach forintegrating performance optimization techniques with compensationpractices, thereby creating an innovative rewards system to driveresults from these individuals, which, for simplicity, are collectivelyreferred to herein as “agents.” While designed to inspire and motivateagents to achieve strategic goals in the client service industry (i.e.,for an organization's clients), this approach also creates an effectiveplatform for coaching employees to increase performance. With respect tothe former, the present invention results in performance optimizationbeing a daily, weekly, and/or monthly event.

The present invention, in embodiments also provides for incentivizingagents that are paid with an hourly wage or another form of a fixedsalary. Previously, it has been difficult to motivate agents based ontheir base pay. Using embodiments of the present invention describedbelow, hourly or fixed salary agents have adjustments or changes totheir base salary (pay) tied to their performance in relation to metricsaligned with goals of an organization. If an agent continues to performat increasingly higher levels of performance, their base salary (orperformance consistency incentive in international countries) willincrease. In some embodiments, if an agent's performance continuallydeclines their base salary (or performance consistency incentive ininternational countries) will decrease. These adjustments can bedesigned to occur automatically, without any input from a supervisor, sothat an agent can feel confident that once they reach a particular levelof performance, they are guaranteed an increase in their salary.

The performance optimization approach involves monitoring performance ofcertain tasks by agents against a defined set of metrics that are linkedto financial aspects concerning the agents over a given period in time.With respect to customer service agents and teams, exemplary metricsinclude, but are not limited to, call resolution statistics (e.g.,statistics that relate to the extent to which a customer service agentor team of agents resolve calls without customers having to call back,i.e., “first call resolution”), customer satisfaction statistics,revenue statistics, attrition statistics, call reduction statistics(e.g., statistics that relate to whether a customer service agent orteam of agents address customers' multiple concerns or questions in asingle call) and quality assessment statistics.

In accordance with an embodiment, the financial aspects relate tocompensation such as, for example, variable compensation and basecompensation, thereby providing an indication of individual performancerelative to compensatory expectations. For example, while one agent'smonthly performance may be exceptional relative to his or hercompensation for that month; another agent having the same exact monthlyperformance may lag behind expectations because of his or her highercompensation. In addition to monitoring individual agent performance,the present invention also relates to monitoring performance of a groupof agents as a whole such as for example, a team of agents or a projector other business entity. For illustrative purposes, these “agents” aredescribed herein as being customer service agents employed by an“outsourcing” company to perform customer service tasks for a “client”company, however the present invention is not limited thereto. In otherembodiments, the present invention may be applied to any type ofemployee including retail employees.

In accordance with this illustrative embodiment, the performanceoptimization approach of the present invention generally providesinspiration and motivation for agents to achieve the strategic goals ofthe client company. Not only does performance management become a daily,weekly, and/or monthly event, but this approach provides an effectiveplatform for training and coaching. In an embodiment, the performanceoptimization approach is implemented on a computer-based system andavailable to agents, team leaders (e.g., supervisors) and management toaccess at any given time. However, Applicant's inventive concept forperformance optimization is also applicable in non-computingenvironments. Accordingly, the present invention is embodied in aconceptual business model in addition to a computer-basedimplementation, each of which is described in turn below and thendescribed in detail as combined with one another.

I. Business Model Approach for Performance Optimization

In an embodiment, the performance optimization (PO) business model 180,which in commerce is referred to as “OPTIMUM REWARDS™,” is based on aframework having a “performance metric” component 182, a “variable pay”component 184 and a “base pay” component 186. The performance metriccomponent 182 involves processes that include analyzing contractualexpectations, determining ROI, selecting applicable metrics, settingachievement levels, communicating achievement levels to agents,providing feedback/coaching, and delivering rewards, which offers agentsan incentive to excel in their work to ultimately drive companyperformance. The defined metrics may relate to any performanceconsideration and, in an embodiment, are based on strategic goals andexpectations with regard to tasks that agents are employed to perform onbehalf of an organization. In alternative embodiments, the metricrelates to tasks that agents are employed to perform on behalf of aclient of the organization. Such business relationships are commonparticularly in the customer service industry in which contractingcompanies employ customer service agents to take calls from othercompanies' customers. However, the PO business model 180 is useful inany relationship where an agent is employed to perform tasks.

Referring back to the framework, the variable pay component 184determines whether and to what extent an agent is entitled to variablepay based on their achievement level of defined performance metrics fora period of time (e.g., daily, weekly, or monthly). The base paycomponent 186 determines each agent's base compensation package bytaking into account each agent's consistent level of achievement overtime (e.g., daily, weekly, or monthly). The performance metric component182, the variable pay component 184 and the base pay component 186 arefurther described below in turn:

The performance metric component 182 provides an illustration of thecombination of a unique systematic process to set metrics, communicateachievement levels to agents, provide feedback/coaching, and delivermeaningful rewards, which motivates and inspires employees to excel intheir work. Performance optimization thus becomes self-directed in thatemployees are given access to near real-time performance and tools toincrease performance at their desktop. Furthermore, this componentallows performance optimization to be near real-time and focused onimproving performance.

In an embodiment, the variable pay component 184 rewards agents based ontheir achievement level of defined performance metrics each month.Examples of features of the variable pay component 184, for oneembodiment, are provided below:

-   -   1) One to four key performance metrics are chosen that align        individual agent performance with a company's strategic goals        which produces desired results.    -   2) Within the plan design, four achievement levels are defined,        which focuses agents on achieving a higher level of performance        each month.    -   3) To qualify for a specific achievement level, participants        must achieve the required results for all chosen key performance        metrics.    -   4) In addition to individual achievement levels, team modifiers        can be added to the plan to reward team success. Only team        members who receive an individual award are eligible for the        team award modifier.    -   5) To be eligible for variable pay, employees must meet one or        more qualifying metric goals such as, schedule adherence, which        acts as a trigger for any variable pay payment.

In some embodiments, variable pay may be defined as a percentage of basepay. For example, variable pay may be defined as 5%, 10%, 15%, or 20% ofbase pay.

In an embodiment, the base pay component 186 is linked to an agent'sconsistent level of achievement over time. Examples of features of thebase pay component 186, for an embodiment, are provided below:

-   -   1) Agents are paid an initial hourly base pay rate corresponding        to an achievement level.    -   2) Agents' hourly base pay rate is subject to increases or        decreases which are linked to consistent achievement of the        chosen performance metrics.    -   3) In order to receive a base pay rate increase, agents must        achieve a higher level of performance than the level        corresponding to their current pay for three consecutive months.        Similarly, an agent's base pay rate will be decreased (but never        below the initial hiring rate) in the event that their level of        performance falls below the associated performance level of        their current base pay rate for three consecutive months.

In some embodiments, the PO business model 180 is embodied in a numberof different methods that may relate for example to managing theperformance of an agent and providing incentives to an agent to increasetheir performance. As one example, FIG. 2 is a flow diagram illustratingoperational characteristics of a method 200, embodying the PO businessmodel 180, for managing the performance of an agent. The method 200 isdescribed below with reference to only one agent and one metric forsimplicity purposes; however, it should be appreciated that in someembodiments the process is practiced in numerous instances for eachagent in an organization and may involve defining a number of differentmetrics. Moreover, the process is described with respect to an agentemployed by an organization. However, in other embodiments it is appliedto an agent employed by an organization to perform tasks for a client ofthe organization. It should be understood that although the steps ofmethod 200 are described in a particular order, in other embodimentssome of the steps may be performed in a different order.

Method 200 begins with a define step 202, which defines a metric that isrelated to a goal of an organization. The metric is a measurablequantity that correlates to achieving a specific goal of anorganization. For example, in one embodiment an organization may have agoal to reduce the number of service calls that a customer must make toget an issue resolved. A metric that may be defined (at step 202) thatrelates to that goal may be referred to as “first call resolution,”which is measured by how many customers call a second time, within 24hours, after calling a first time. As another example, an organizationmay have a goal of increasing revenue. A metric that may be defined (atstep 202) that relates to that goal may be referred to as“cross-selling,” which is measured by sales revenue generated fromcustomer service calls. These are merely some examples of metrics thatmay be defined in relation to goals of an organization. Those with skillin the art will appreciate that the specific metrics defined at step 202will relate to the specific goals of the organization and are notlimited to the examples described above.

After step 202, a second define step 204, is performed to define aplurality of performance levels for the performance metric defined atstep 202. The performance levels are intended to represent a relativelevel of performance of an agent for the metric defined in step 202. Inone embodiment, the performance levels may be defined as belowthreshold, threshold, target and stretch. As those with skill in the artwill appreciate, the number of levels as well as the labels applied tothe levels is a matter of preference and any number of levels referredto with any label may be defined at step 204. Each of the performancelevels defined at step 204 is associated with an achievement value forthe performance metric. The achievement values are established at step206.

At step 206, the achievement values associated with the performancelevels defined at step 204 are established based on factors such as theexperience level of an agent. The achievement values are values that anagent must achieve, for a defined metric, in order for their performanceto be classified/categorized within one of the defined performancelevels. In one embodiment, average call handling time may be defined asa metric, and the performance levels may be defined as below threshold,threshold, target, and stretch. In this embodiment, at step 206,achievement values of: >360 seconds, 360 seconds, 340 seconds and 320seconds are established for the defined performance levels of: belowthreshold, threshold, target, and stretch, respectively. Accordingly,for an agent's performance to be classified as threshold the agent mustachieve an average call time that does not exceed 360 seconds. If anagent's average call time is less than the 320 seconds value, theirperformance will be classified as stretch (performance level).

The achievement values established at step 206 are based on contractualor strategic goals and can be adjusted based on the experience of anagent. For example, if a first agent has more experience than a secondagent, the achievement values established for the first agent couldrequire a better agent performance for each performance level in orderto reflect the higher experience of the first agent. From theperspective of an organization, setting of the achievement values inrelation to experience is an effective way to tie an agent'stenure/experience to performance. Referring back to the previousexample, an agent that is more experienced may have average callhandling time achievement values established at step 206 of: >340seconds, 320 seconds, 310 seconds and 300 seconds for the definedperformance levels of: below threshold, threshold, target, and stretch,respectively.

After the achievement values have been established at step 206, acompensation rule is provided at step 208. The compensation rule defineswhich of the performance levels an agent must achieve to change theircurrent compensation, as well as the change to an agent's compensation.The change may be an increase or a decrease in the current compensationof an agent, or in a component of their compensation (e.g., base pay orvariable pay). In one embodiment, the compensation rule may provide forincreasing the compensation of an agent if an agent achieves aperformance level above the threshold performance level. In analternative embodiment, the compensation rule may provide for decreasingthe compensation of an agent if an agent achieves the below thresholdperformance level. In some embodiments, the change in compensation maybe reflected in the variable component 184, described above with respectFIG. 1, such as may be the case when providing a bonus to an agent whoachieves a performance level above the threshold performance level. Inother embodiments, the change in compensation may be reflected in thebase pay component 186, described above with respect to FIG. 1.

In some embodiments, the compensation rule may define a time over whichan agent must achieve a particular performance level to change theircurrent compensation. For example, the compensation rule may define thatan agent must achieve a performance level above the thresholdperformance level for three months to increase their currentcompensation, or a portion of their compensation, such as their basepay. In another example, the compensation rule may define that an agentmust achieve a performance level below the threshold performance levelfor three consecutive months to have some portion of their compensationreduced. In some embodiments, the compensation rule may define two ormore periods of time over which an agent must achieve a particularperformance level to change their current compensation. In oneembodiment, a compensation rule may define a first time (e.g., a month)over which an agent must achieve a level above the threshold level toreceive a bonus (variable pay); a second time (e.g. three months) overwhich an agent must achieve a performance level above the thresholdperformance level to increase their base pay; and a third time (e.g. twomonths) over which an agent must achieve a performance level less thanthe threshold performance level to decrease their base pay.

In one embodiment, the compensation rule is designed to account for anorganization's concern over profits. As one example, in the customerservice industry a client may contract an organization which employscustomer service agents to take calls from the client's customers. Inthis example, the client may pay the organization a set amount of moneyper agent. The more an agent is paid by the organization, the less theorganization will make as profit. Accordingly, the compensation rule maybe adapted to reflect this. In one embodiment, an agent must achieve aperformance level above a defined performance level, e.g. the thresholdperformance level, to increase their base pay. However, when their basepay increases, the amount available for variable pay will decrease. Forexample, an agent may have a base pay of $10.00/hour and the potentialfor receiving a variable pay amount that is 20% of their base pay. Ifthe agent performs at a high level for a predetermined period of time,their base pay may increase to $11.00/hour, however their potentialvariable pay may be reduced to only 10% of their base pay. This type ofcompensation rule still incentivizes agents, because their base pay(i.e., guaranteed money) is increased with better performance, but alsotakes into consideration the costs/margins of an organization. It iscontemplated that other compensation rules may be defined to apply tovarious situations, and the present invention is not limited to anyspecific compensation rule.

After the compensation rule has been provided at step 208, step 210 isperformed to monitor an agent with respect to the performance metric(defined at step 202). Step 210 may be performed in any suitable waysuch as collecting and aggregating data for an agent. As those withskill in the art will appreciate, the specific steps that are performedwill depend on the metrics defined at step 202. As one example, if ametric is defined as average call handling time, step 210 will includemonitoring the average call handling time of an agent. The monitoring ofaverage call handling time may be performed by monitoring eachindividual call time and obtaining an average of each individual calltime. In an alternative embodiment, the average call time may becalculated by monitoring the total call time and the total number ofcalls, and calculating the average call time by dividing the total calltime by the total number of calls. As another example, if first callresolution is defined as a metric, step 210 may include monitoringwhether a customer who calls a first time must call a second time toresolve the problem.

In embodiments, step 210 results in obtaining an agent performance. Theagent performance represents the performance of an agent with respect toa defined metric. In some embodiments, the agent performance is definedas a quantifiable, objective value, e.g., average call time, number ofcalls handled, first call resolution, revenue etc. In other embodiments,the agent metric is represented as a numeric value, but may have asubjective component. For example, an agent's performance with respectto customer satisfaction may be rated using a numeric scale, e.g., ascale from one to five. An agent's performance may be used in someembodiments in step 212 to categorize/classify an agent's performancewithin one of the performance levels.

At step 212, the agent performance generated during step 210 is comparedto the achievement values to determine an agent performance level. Theachievement values are used to determine which of the performance levelsan agent's performance should be classified within. Generally, at step212 an agent's data is compared to the achievement values to determinewhich of the achievement values has been met. The agent's performance isthen classified as falling within the performance level associated withthe met achievement value. Expanding on a previous example forillustrative purposes, if an agent's average call time (agentperformance metric) is below the achievement value associated with the“target” performance level, then the agent's performance with respect tothe metric, average call handling time, will be classified as “target.”

At step 214, the performance results for a group of agents, such as allthe agents in a business organization, is evaluated. Step 214 involvesaggregating the performance of a number of agents to determine how manyare performing at each performance level defined at step 202. Inembodiments, step 212 may involve evaluating groups of agents based onan entire business organization, teams, projects, clients for which theagents are working, sites, or regions.

In embodiments, step 214 provides for evaluating different groups ofagents in a normalized way. That is, since all of the agents areevaluated using the same performance levels (e.g., below threshold,threshold, target and stretch), a normalized comparison can be made todetermine which groups are performing better relative to other groups.For example, if a group of agents (team 1) is working on a project, anda second group (team 2) is working on another project, at step 214 acomparison between the two teams can be made to determine which team isperforming at a relatively higher level, such as which team has moreagents performing at stretch or which team has less agents performing atbelow threshold. In embodiments, the two teams may have differentmetrics, different achievement values, and compensation levels, howeverbecause the performance levels are the same the normalized comparisoncan be made. This embodiment may be particularly useful to managers whoneed to decide which group of agents need additional coaching orsupport. The ability to compare groups of agents in a normalized wayallows managers to decide which groups of agents they should directtheir efforts toward for improving performance.

Method 200 described above with respect to FIG. 2 is simply one methodthat implements PO business model 180. In other embodiments, method 200may include more, or less, steps than those described above with respectto FIG. 2, or the steps may be performed in different order. For examplein one embodiment, step 214 may be followed by an applying step whichautomatically applies the compensation rule based on the agentperformance level to change the current compensation provided to theagent. Applying of the compensation rule may occur automatically withoutany input by a human supervisor. In other embodiments, the step 214 maybe followed by an evaluating step. The evaluating step may be performedby a human supervisor to determine whether the compensation rule shouldbe applied. In other embodiments, the evaluating step may be performedto determine whether/how a supervisor should provide coaching or otherfeedback to the agent.

As another example, illustrated in FIG. 2 as steps 216 and 218 shown indashed lines, method 200 may include additional steps such ascommunicating the compensation rule to the agent 216 and providingaccess to performance information to the agent 218. The performanceinformation may relate to, for example, the agent performance,achievement values, and agent performance level. In this embodiment, theadditional steps tend to incentivize an agent, because they are aware ofhow their compensation is affected by their performance and have accessto their performance information.

In embodiments, method 200 may include steps for changing theachievement values. In one specific embodiment, if an agent'scompensation is changed as a result of their performance, theachievement values are adjusted to reflect the change in the agent'scompensation. That is, if an agent gets an increase in theircompensation (e.g., increase in base pay) the achievement values arechanged so that an agent must perform at a higher level than before toachieve each of the performance levels. In other embodiments, theachievement values may be changed based on the performance of a group ofagents, such as a team or the entire organization. As one example, anaverage agent metric for a group of agents may be compared over a periodof time (e.g., several months). If the comparison indicates that theagents' performance as a group is showing a trend, the achievementvalues may be changed as a result of the trend. The threshold values maybe changed to require the agents to perform at a relatively higher levelto achieve the performance levels.

It should be understood that the foregoing description of PO businessmodel 180 and method 200 implementing PO business model 180 are forillustrative purposes only. The following description includesdiscussion of PO business model 180 as implemented using acomputer-based approach. The present invention contemplates that in someembodiments the steps described above, made without reference to acomputer-based approach, and the steps described below with respect tothe computer-based approach may be combined in a variety ofcombinations, and may be implemented with or without the use of acomputer system.

II. Computer-Based Approach for Performance Optimization

In accordance with an embodiment, the PO business model 180 describedabove is embodied within a software application 110 implemented in adistributed computing environment 100, as shown in block diagram form inFIG. 3. The distributed system 100 includes a plurality of clientcomputers 101, 102, 104 and 105, a communications network 106(hereinafter, “network”), a server computer 108, and a database 114. Theperformance optimization software application 110 resides on the servercomputer 108 and is accessible to any of the plurality of clientcomputers 101, 102, 104 and 105 by way of the communications network106. The software application 110 may be activated, controlled andmanipulated by users on the client computers 101, 102, 104 and 105 atremote locations using conventional networking technologies.Furthermore, browser applications (not shown) are implemented on theclient computers 101, 102, 104 and 105 and used to render electronicresources (e.g., web pages) containing information related toperformance management. For simplicity and clarity, the softwareapplication 110, which is described in detail below in connection withFIG. 3, is hereinafter referred to as a “performance optimizationapplication 110.”

As depicted in FIG. 3, the distributed system 100 may be thought of ashaving two distinct components: “front-end” client computers 101, 102,104 and 105 and the “back-end” server computer 108 on which theperformance optimization application 110 is implemented. In accordancewith an embodiment of the present invention, the back-end servercomponent 108 can be a personal computer, a minicomputer, or a mainframethat performs, among other functions: data managing, client informationsharing, security services and administration functions related to theperformance optimization application 110. A server farm (not shown) mayalternatively be used. The distributed system 100 is not limited to anyparticular implementation and instead embodies any computing environmentupon which functionality of the environment may be practiced.

While only four client computers 101, 102, 104 and 105 are shown, itshould be appreciated that the distributed system 100 may include anynumber of client computers. For example, in an embodiment, thecommunications network 106 may be the Internet or, alternatively, anIntranet, wherein the server computer 108 is a central server on whichthe performance optimization application 110 resides and is specificallyidentified to have a network location expressed as a Uniform ResourceLocator, or URL. Accordingly, implementation of the performanceoptimization application 110 renders a web site or, alternatively,Intranet site, identified by the URL and hereinafter referred to fornomenclature purposes as a “performance optimization website.” Theclient computers 101, 102, 104 and 105 thus represent computersconnected to the communications network 106 through any conventionalmeans such as, for example, routers and switches. Accessing theperformance optimization application 110 therefore involves a user(either an agent, team leader or management) activating a browserapplication (not shown) on a client computer 101, 102, 104, 105 anddirecting the browser application to the URL specified for theperformance optimization application 110. As shown in FIG. 3, agentsaccess the performance optimization application 110 using the clientcomputer 102; team leaders access the performance optimizationapplication 110 using the client computer 104 and management access theperformance optimization application 110 using the client computer 105.Also, shown in FIG. 3 is client computer 101, which allows anadministrator to access the performance optimization application 110.

When accessed by a user (e.g., agent, team leader, management, oradministrator as described above) over the communications network 106,the performance optimization application 110 renders the aforementionedperformance optimization website, which includes various forms ofinformation and functionality related to performance management bothfrom an individual standpoint and a collective (i.e., team-based andorganization-based) standpoint. Based on website manipulation by theuser, the performance optimization application 110 retrieves suchinformation from the database 114 via network 112 (e.g., an intranet)or, alternatively, from local cache memory, and provides thatinformation to the user's browser for rendering therein.

With reference now to FIG. 4, the performance optimization software 110is described in more detail with reference to information andfunctionality provided by the software 110 in accordance with anembodiment of the present invention. Specifically, in accordance withthis embodiment, the performance optimization software 110 includes anagent interface 116, a team leader interface 118, a management interface120, and an administrator interface 150. The performance optimizationsoftware application 110 may be referred to in commerce as “EMPOWER™”and, similarly, the agent interface 116, the team leader interface 118and the management interface 120 are referred to as “EMPOWER1™,”“EMPOWER2™” and “EMPOWER3™,” respectively.

The performance optimization software application 110 provides specificinterfaces 116, 118, 120, and 150 and associated levels of access tousers based on whether the users are agents, team leaders, management,or administrators. Each interface 116, 118 120, and 150 embodies one ormore electronic resources that provide information and/or functionalityspecifically intended and authorized for one of these specific types ofusers. When accessed by a user, an instance of the performanceoptimization website is created on the server computer 108 and one ofthese interfaces (116, 118, 120, or 150 is activated to renderelectronic resources relevant for that user. For example, if the user isan agent, the agent interface 116 is activated to render electronicresources (e.g., web pages) specifically configured (in content andformat) to that agent.

With specific reference to these interfaces 116, 118, 120, and 150 theagent interface 116 provides agents with access to informationconcerning their specific performance relative to a certain timeincluding an indication of how their performance affects, could affect(if maintained) and/or has affected their compensation. In anembodiment, performance is measured against a set of defined metricsand, as such, the agent interface 116 provides agents with an indicationof how their performance ranks against the defined metrics during agiven time period (e.g., day, week, month, year). This information maybe presented in numerous different formats and, to accommodate theformat in which the information is displayed, the agent interfaceincludes user interface features, generally shown as 122, 124, 126 and128, which provide agents with the ability to view the information in avariety of formats and details. Table 1 below illustrates an example ofa graphical representation that may be displayed by interface 116 insome embodiments (in other embodiments Table 1 may be displayed byanyone of interfaces 116, 118, 120, or 150). Table 1 illustrates agraphical representation that relates a performance level achieved by anagent to a time period, in this case a month over which the agentachieved the performance level. In other embodiments, the graphicalrepresentation may relate the performance level achieved by an agent tothe day the agent achieved the performance level (e.g., a calendar witha graphic indicating an achieved level for each day of a month.). Also,in other embodiments, Table 1 may relate to a group of agents (i.e., ateam) or an organization as a whole.

TABLE 1 January February March April Stretch Target Threshold BelowThreshold

In some embodiments, agent interface 116 provides for displaying agraphical representation of an agent's achieved metric relative to oneor more achievement values. This allows the agent to easily determinehow to change their behavior (e.g., spend less time on a call) so thatthey can achieve a desired achievement level and therefore performancelevel. For example, agent interface 116 may display a graphicalrepresentation, such as a bar graph with four bars that representachievement values. In this embodiment, the bar graph will also includeone bar showing the agent's performance metric. This graphicalrepresentation allows a viewer (e.g., an agent or supervisor) to easilysee, where the agent's metric is in relation to achievement values.

The team leader interface 118 allows each individual responsible forsupervising tasks of a team of agents to access information concerningthe performance of his or her group as a whole. As noted above, suchperformance is measured against a defined set of metrics in accordancewith an embodiment. Additionally, the team leader interface 118 providesthese individuals access to the agent interface 116 such that they areable to access performance information concerning each of the agentswithin their team. The team leaders are only authorized to use the agentinterface 116 to view information concerning the agents associated withtheir team. This information may be presented in numerous differentformats and include user interface features, generally shown as 132,130, and 134, which provide team leaders with the ability to view theinformation in a variety of formats with varying degrees of detail.

In contrast, the management interface 120 is associated withunrestricted authorization to performance information and providesaccess to such information concerning each individual agent, each teamof agents and, collectively, all agent teams as a whole. The managementinterface 120 therefore provides its authorized users with access toperformance information for the entire company or organization as wellas access to the agent interface 116 and the team leader interface inorder to view performance data for agents and teams, respectively. Thisinformation may be presented in numerous different formats and includeuser interface features, generally shown as 136, 138, and 140.

Administrator interface 150 is associated with unrestrictedauthorization to performance information and provides access to suchinformation concerning each individual agent, each team of agents and,collectively, all agent teams as a whole. Additionally, theadministrator interface 150 provides authorized users with privileges toestablish, modify, or remove performance metrics, performance levels,and compensation rules. Administrator interface 150 also providesauthorization to change information about agents, such as adding orremoving agents or teams of agents from application 110. Administratorinterface 150 includes user interface features, generally shown as 152,154, and 156. As those with ordinary skill in the art will appreciate,administrator interface 150 is also used to perform generaladministrative tasks that may be required on application 110.

In an embodiment, the present invention is practiced as a method fordetermining whether a user requesting access to the performanceoptimization software application 110 is an agent, a team leader,management, or an administrator, and based on the determined type ofuser, the method returns the appropriate interface 116, 118, 120, or150.

The graphical representations described above, and those furtherdescribed below, are also useful in methods and processes that are notimplemented using computer systems. As mentioned above, it iscontemplated that in some embodiments the present invention will combinefeatures, aspects, components, steps, and processes described hereinwith respect to the computer implemented methods, with those describedabove without the use of computer systems.

With the various software components of the performance optimizationsystem 110 described in detail above, attention is now turned to adetailed illustration of the various components of the exemplaryoperating environment on which the performance optimization application110 is at least partially implemented, i.e., the sever computer 108.Exemplary elements of a server computer 108 are shown in FIG. 5 whereinthe processor 401 includes an input/output (I/O) section 402, amicroprocessor, or Central Processing Unit (CPU) 403, and a memorysection 404. The present invention is optionally implemented in thisembodiment in software or firmware modules loaded in memory 404 and/orstored on a solid state, non-volatile memory device 413, a configuredCD-ROM 408 or a disk storage unit 409.

The I/O section 402 is connected to a user input module 405, e.g., akeyboard, display unit 406, etc., and one or more program storagedevices, such as, without limitation, the solid state, non-volatilememory device 413, the disk storage unit 409, and the disk drive unit407. The solid state, non-volatile memory device 413 is an embeddedmemory device for storing instructions and commands in a form readableby the CPU 403. In accordance with various embodiments, the solid state,non-volatile memory device 413 may be Read-Only Memory (ROM), anErasable Programmable ROM (EPROM), Electrically-Erasable ProgrammableROM (EEPROM), a Flash Memory or a Programmable ROM, or any other form ofsolid state, non-volatile memory. In accordance with this embodiment,the disk drive unit 407 may be a CD-ROM driver unit capable of readingthe CD-ROM medium 408, which typically contains programs 410 and data.Alternatively, the disk drive unit 407 may be replaced or supplementedby a floppy drive unit, a tape drive unit, or other storage medium driveunit. Computer readable media containing mechanisms (e.g., instructions,modules) to effectuate the systems and methods in accordance with thepresent invention may reside in the memory section 404, the solid state,non-volatile memory device 413, the disk storage unit 409 or the CD-ROMmedium 408. Further, the computer readable media may be embodied inelectrical signals representing data bits causing a transformation orreduction of the electrical signal representation, and the maintenanceof data bits at memory locations in the memory 404, the solid state,non-volatile memory device 413, the configured CD-ROM 408 or the storageunit 409 to thereby reconfigure or otherwise alter the operation of theserver computer 108, as well as other processing signals. The memorylocations where data bits are maintained are physical locations thathave particular electrical, magnetic, or optical propertiescorresponding to the data bits.

In accordance with a computer readable medium embodiment of the presentinvention, software instructions stored on the solid state, non-volatilememory device 413, the disk storage unit 409, or the CD-ROM 408 areexecuted by the CPU 403. In this embodiment, these instructions may bedirected toward monitoring performance of individual agents, a team ofagents or an organization as a whole as described and shown in detailwith reference to FIGS. 1-4 and 6-9. Data used in the analysis of suchapplications may be stored in memory section 404, or on the solid state,non-volatile memory device 413, the disk storage unit 409, the diskdrive unit 407 or other storage medium units coupled to the servercomputer 108.

In accordance with one embodiment, the server computer 108 furthercomprises an operating system and one or more application programs. Suchan embodiment is familiar to those of ordinary skill in the art. Theoperating system comprises a set of programs that control operations ofthe server computer 108 and allocation of resources. The set ofprograms, inclusive of certain utility programs, also provide agraphical user interface to the user. An application program is softwarethat runs on top of the operating system software and uses computerresources made available through the operating system to performapplication specific tasks desired by the user. The operating system isoperable to multitask, i.e., execute computing tasks in multiplethreads, and in accordance with a preferred embodiment is the Microsoft.Net Framework running on the Microsoft Windows 2000 or 2003 serverplatform. It should be appreciated, however, that other operatingsystems are contemplated within the scope of the present invention suchas, without limitation, IBM's OS/2 WARP, Apple's MACINTOSH OSX operatingsystem, Linux, UNIX, etc.

In accordance with yet another embodiment, the processor 401 connects tothe communications network 412 by way of a network interface, such asthe network adapter 411 shown in FIG. 5. Through this networkconnection, the processor 401 is operable to transmit within thedistributed system 100, as described, for example, in connection withthe client computers 102 and 104 exchanging data with the servercomputer 108.

With the computing environment of FIG. 5 in mind, logical operations ofthe various exemplary embodiments described below in connection withFIGS. 6, 7 and 9 may be implemented: (1) as a sequence of computerimplemented acts or program modules running on a computing system;and/or (2) as interconnected machine logic circuits or circuit moduleswithin the computing system. The implementation is a matter of choicedependent on the performance requirements of the computing systemimplementing the invention. Accordingly, the logical operations makingup the embodiments described herein are referred to variously asoperations, structural devices, acts or modules. It will be recognizedby one skilled in the art that these operations, structural devices,acts and modules may be implemented in software, in firmware, in specialpurpose digital logic, and/or any combination thereof without deviatingfrom the spirit and scope of the present disclosure as recited withinthe claims attached hereto.

Accordingly, the various embodiments of the present invention may beimplemented as a computer process, a computing system or as an articleof manufacture, such as a computer program product or computer-readablemedia. The computer program product may be a computer storage mediareadable by a computer system and encoding a computer program ofinstructions for executing a computer process. The computer programproduct may also be a propagated signal on a carrier readable by acomputing system and encoding a computer program of instructions forexecuting a computer process.

III. Combined Implementation of the PO Business Model and Computer-BasedPerformance Optimization System

FIG. 6 describes an optimization process 500 for implementing the PObusiness model 180 in conjunction with the performance optimizationsoftware application 110 to provide users with a computer-based systemfor optimizing performance in accordance with an embodiment of thepresent invention. As such, the optimization process 500 is operable toevaluate an agent's, team's or entire organization's performance againstrelative criterion, or metrics, and link such evaluation to financialconsiderations, as described above. With that said, the optimizationprocess 500 is described below with reference to only one agent forsimplicity purposes; however, it should be appreciated that the processis preferably practiced in numerous instances for each agent in anorganization. The optimization process 500 is performed using anoperation flow that begins with a start operation 502 and ends with afinish operation 514. The start operation 502 is initiated to beginmonitoring performance of a specific agent in an organization. From thestart operation 502, the operation flow initially passes to a firstdefine operation 503.

The first define operation 503 establishes compensation levels, each ofwhich may include, without limitation any of the following: base pay,actual or expected variable pay (e.g., bonuses, in-kind compensation,stock options, etc.) or any other compensation. In an embodiment, thefirst define operation 503 defines a number of compensation groups, or“compensation levels.” For example, these compensation levels mayinclude the following four different categories ranging from therelative lowest compensation packages of all agents to the relativehighest compensation packages of all agents in the organization:learning, successful, successful+, and role model. At step 503, anagent's current compensation level can be set to one of the definedcompensation levels. After the agent's compensation level has beendefined, the operation flow passes to a second define operation 504.

The second define operation 504 establishes one or more performancemetrics for the agent. The performance metrics may relate to any numberof performance-based considerations such as, without limitation, callresolution statistics, customer satisfaction statistics, revenuestatistics, attrition statistics, call reduction statistics and qualityassessment statistics. In an embodiment, performance levels are defined(as described above in FIG. 2 step 204) and achievement valuescorresponding to each performance level are also defined (FIG. 2 step206). In a further embodiment, each compensation level may havedifferent amounts of possible variable pay that may be received forreaching the achievement values. As such, two agents at differentcompensation levels may have the exact same responsibilities but wouldhave differing possible variable pay amounts. With that said, anembodiment of the present invention involves setting an agent's possiblevariable pay level based on the compensation level within which theagent's current compensation level is categorized. After the one or moreperformance metrics have been defined for the agent, the operation flowpasses to a collect operation 506 as the agent begins working for theorganization and accomplishing tasks.

The collect operation 506 collects actual performance statisticsassociated with the accomplishment of tasks by the agent. For example,if the agent is a customer service agent, the collect operation 506 maycollect information embodying the number of calls that the agentdisposes without the assistance of any other agents (i.e., first callresolution and call reduction). Collecting the performance statistic atstep 506 also involves generating an agent performance with respect tothe metrics. That is, for each metric an agent performance (or value)with respect to that metric is generated at step 506. In an embodiment,the operation flow is maintained at the collect operation 506 andperformance statistics are collected until a request is made by anagent, his or her team leader or management to monitor performance ofthat agent or his/her team, at which time, the operation flow passes toan analysis operation 508. Alternatively, the collect operation 506 mayperform statistics collection for a predetermined period of time (e.g.,daily), the conclusion of which passes the operation flow to theanalysis operation 508.

Regardless of the implementation, the operation flow passes from thecollect operation 506 to the compare operation 508, which compares theagent performance against the achievement values from step 504 todetermine the relative extent to which the agent is performing for themetrics set by the define operation 504. With that said, an embodimentof the present invention involves ranking the agent's performance intoone of four performance categories, or “performance levels:” belowthreshold, threshold, target and stretch. After the agent's performancehas been ranked and categorized into one of the four “performancelevels,” the operation flow passes to an evaluate operation 510.

The evaluate operation 510 involves integrating and analyzing theagent's performance with the specified financial considerations, whichmay include any one or more of the following: compensation levelincluding the agent's base pay, the agent's variable pay (e.g., bonuses,in-kind compensation, stock options, etc.) or expected variable pay, acombination of both or the agent's entire compensation package, asdefined in the first define operation 503. For exemplary purposes, theoptimization process 500 is described herein with the evaluate operation510 integrating the agent's performance with his or her compensationpackage. That is, the evaluate operation 510 creates a representation inmemory (e.g., on the server computer 108) of how the agent's performancecompares with his or her compensation package for analysis as to therelative expected performance of the agent. From the evaluate operation510, the operation flow passes to a display operation 512.

The display operation 512 renders the integrated information created bythe merge operation 510 in a manner for display on a browser or otherapplication of one of the client computers 102, 104 and 105. In anembodiment, such rendering involves creating and displaying a graphicalrepresentation comparing or otherwise relating the performance resultsto financial considerations specifically associated with the agent.Accordingly, the display operation 512 displays the results of theagent's performance in combination with these specific financialconsiderations. In an embodiment, as noted above, these financialconsiderations preferably embody the agent's compensation level. Inaccordance with this embodiment, the graphical representation embodyinga table having columns representing the different compensation bucketsand rows representing the different performance buckets, as shown belowin an example in Table 2:

TABLE 2 Learning Successful Successful+ Role Model Stretch TargetThreshold Below Threshold

Such a table allows for the agent's performance results to be comparedagainst his or her compensation level in a meaningful manner for reviewby the agent, his or her team leader or management. Indeed, while Table2 is described as presenting performance versus financial informationfor only a single agent in order to illustrate the optimization process500 of FIG. 6, embodiments of the present invention involve using suchan integration presentation technique to display information for acollective set of agents (i.e., a “team) or the organization as a whole.With respect to the former, the display operation 512 renders agraphical representation comparing or otherwise relating the performanceresults of an entire team of agents to financial considerationsspecifically associated with the team (e.g., the collective compensationpackage of the team). With respect to the latter, the display operation512 renders a graphical representation comparing or otherwise relatingthe performance results of an entire organization (e.g., a plurality ofteams) to financial considerations specifically associated with theorganization (e.g., the collective compensation package of theorganization). Accordingly, Table 2 is applicable for display throughnot only the agent interface 116, but also the team leader interface 118(to display performance versus financial information for individualagents and teams as a whole) and the management interface 120 (todisplay performance versus financial information for individual agents,individual teams and the organization as a whole). From the displayoperation 512, the operation flow concludes at the terminate operation514.

Turning now to FIG. 7, a process 600 for rendering display of anappropriate interface (e.g., 116, 118 or 120) for a user of theperformance optimization software 110 is shown in accordance with anembodiment of the present invention. The rendering process 600, whichembodies the display operation 512 shown in FIG. 6, is described in anexemplary embodiment as being performed by the server computer 108 torender a performance optimization website on a browser application. Forillustration purposes, the browser application is described herein asbeing implemented on one of the client computers 102, 104 and 105communicatively connected to the server computer 108 via the network106. However, in accordance with an alternative embodiment, the browserapplication may be implemented on a client computer or other userterminal locally connected to the server computer 108 by way of theintranet 112. Such an embodiment is particularly useful in circumstanceswherein a team leader or management is accessing the performanceoptimization software 110 from client computer located on-site with theserver computer 108 (e.g., an organization's campus). Regardless ofimplementation, the process 600 is performed using an operation flowthat begins with a start operation 602 and ends with a finish operation614.

The start operation 602 is initiated in response to a user requestingaccess to the performance optimization application 110 through one ofthe client computers 102, 104 or 105. Accordingly, the start operation602 is triggered in response to the user entering the URL of theperformance optimization application 110 into the browser application,which then through conventional networking technology, directs therequest to the server computer 108. In response, the performanceoptimization website is rendered in the browser application andavailable for use by the user. The performance optimization websiteprovides access to the three different interfaces 116, 118 and 120,which, as described above, are each associated with a different level ofauthorized access based on user type (i.e., agent, team leader,management). That is, each agent is only authorized to access the agentinterface 116 and, more particularly, only to their performanceinformation. In contrast, team leaders are authorized to access teamleader interface 118, which provides access to performance informationassociated with their team as well as performance information for allagents on their team. In an embodiment, the latter form of information(i.e., information specific to all agents that report to a team leader)is made available to team leaders by way of the agent interface 116,which is through the team leader interface 118. In further contrast,management for an organization is authorized to access managementinterface 120, which provides performance information associated withthe organization as a whole as well as performance information for eachindividual team and agent. Again, to accomplish the latter, the teamleader interface 118 and the agent interface 116 are both accessible tomanagement through the management interface 120. Because of thesedifferent authorization levels, the initially-rendered webpage, or“homepage,” of the performance management web site includes a userinterface region (i.e., “logon component”) in which authorized users,e.g., agents, team leaders and management, may enter a uniqueidentification name (e.g., PIN) and a password to access their privateand personalized specific information.

After the performance optimization website has been rendered in theuser's browser application, the operation flow of the management process600 passes to a receive operation 604. The receive operation 604 istriggered in response to the user submitting a valid PIN andcorresponding password to the performance optimization application 110via the logon component. In receipt of such authorizing information, theoperation flow passes to a first query operation 606. The first queryoperation 606 determines whether the user is an agent, a team leader ormanagement. In an embodiment, such a determination involvesconsideration of the PIN, which either in memory of the server computer108 or in the database 114, is linked to a designator of the user typeassigned the PIN.

If the first query operation 606 determines that the user is management,the operation flow is passed to a first activate operation 608, whichactivates the management interface 120 to render web pages specificallyintended for management, as described above. If the first queryoperation 606 determines that the user is a team leader, the operationflow is passed to a second activate operation 609, which activates theteam leader interface 118 to render web pages specifically intended torelate to team leaders, as described above. If the first query operation606 determines that the user is an agent, the operation flow is passedto a third activate operation 610, which activates the agent interface116 to render web pages specifically intended to relate to agents, alsoas described above.

After the appropriate interface (116, 118, 120 or 150) of theperformance optimization application 110 has been activated, theoperation flow passes to a second query operation 612. The second queryoperation 612 detects whether the user has logged off of the performanceoptimization website and, if so, passes the operation flow to the finishoperation 614, which terminates, or closes, the activated interface(116, 118, 120, or 150). Otherwise, the operation flow is maintained atthe second query operation 612, which is continuously practiced untilthe user logs off of the performance optimization website.

Attention is now turned to FIGS. 8 and 9, which further illustratecombined implementation of the PO business model 180 and the performanceoptimization software application 110 in accordance with an embodimentof the present invention and, thus, further depict the uniquecombination of performance optimization and rewards with enablingtechnology provided by embodiments of the present invention. FIGS. 8 and9 illustrate that the performance optimization software application 110is designed to enable and automate the PO business model 180, thecombination of which involves data acquisition and aggregation,administration, performance calculation, agent review, supervisor reviewand compensation adjustments, as described in more detail below.

Shown in FIG. 8 is a block diagram of a software environment 700 thatimplements PO business model 180 and the performance optimizationsoftware application 110, according to an embodiment of the presentinvention. Environment 700 includes a number of applications 702, 704,706 and 708, which collects or maintains information that is relevant toperformance of an agent (explained in greater detail below).Additionally, a datamart application 710 acquires and aggregatescollected data from applications 702, 704, 706, and 708 on a dailybasis. The collected data acquired by datamart application 710 is usedby a metric layer 712 to calculate metrics. System 700 also includes anadministration application 714 that is used to predefine the metricscalculated by metric layer 712, and predefine performance/pay criteria,which may be referred to in commerce and herein as paysets, to evaluateagent performance. Application 714 also includes administrator interface150 described above with respect to FIG. 4. PO application 110 will usethe metrics calculated by metrics layer 712 and the predefinedperformance/pay criteria to evaluate agent performance and providecompensation adjustments 716 to payroll application 718, if warranted.

In environment 700, the sources of agent data 702, 704, 706, 708, and709 are intended to generally illustrate systems (e.g., hardware,software application etc.) that contain information that is relevant toevaluating the performance of an agent. Although described belowspecifically with respect to a customer service representative agent, inother embodiments, sources 702, 704, 706, 708, and 709 will collect datathat is relevant to the tasks performed by the specific agents whoseperformance is being managed. Moreover, although sources 702, 704, 706,708 are described as individual applications they may in otherembodiments include several applications and/or include a number ofdifferent modules as well as hardware for implementing the applicationsor modules.

Application 702 is a timekeeping software application that maintains thehours worked by individual agents. For example, an agent may useapplication 702 to clock in when beginning work for the day, and clockout when the work day is over. Scheduling application 704 may includeinformation that indicates the particular schedule that an agent isassigned and expected to work, such as the day of the week with thespecific hours of the day. Application 706, in embodiments, is anapplication that maintains and generates information about specificcalls that are handled by agents. Some examples of information thatapplication 706 collects include call times, number of calls handled,and quality assurance information for calls. In other embodiments,application 708 may collect or maintain other data relevant toevaluating an agent's performance. Agent information may be maintainedand generated by application 710. Agent information may include forexample identifying information for agents employed by an organization.As can be appreciated, applications 702, 704, 706 and 708 all collect ormaintain information that is useful in evaluating an agent.

Daily datamart 710 acquires, aggregates, and stores collected data fromapplications 702, 704, 706 and 708, on a daily basis. The data is merelyreceived and aggregated from applications 702, 704, 706 and 708.Although as is appreciated by those with skill in the art, acquiring andaggregating data from applications 702, 704, 706 and 708 may involve anumber of ETL (extract, transform, load) processes.

The administration application 714 is used to predefine metrics thatwill be used to evaluate agents. As described above, some examples ofmetrics include call resolution, customer satisfaction, revenuegeneration, attrition, call reduction and quality assessment.Administration application 714 is used to define the metrics as afunction of the collected data acquired and aggregated in daily datamart710. For example, using administration application 714, an average callhandle time metric may be defined as a function of: total call timedivided and total number of calls for an individual agent. This ismerely one example, and any metric useful in evaluating an agent can bedefined using administrative application 714 as a function of thecollected data.

The metrics layer 712 uses the collected data to calculate agent metricsaccording to the predefined metrics. As described above, the metrics arepredefined using administration application 714. The metrics layer 712may include one or more applications that take as input the collecteddata from daily datamart 710 and calculates agent metrics according tothe metrics predefined using the administration application. The metricslayer 712 provides the calculated metrics to the PO application 110.

Referring again to administrative application 714, it is also used toestablish paysets. A payset includes key performance indicators definedin terms of levels combined with metrics. In order for an agent toachieve a specific level, he/she must meet or exceed the achievementlevel for all metrics. For example, in an embodiment, there may be fourperformance levels: below threshold, threshold, target and stretch. Tobe rained within a performance level, an agent must achieve or exceedthe specific achievement level for all metrics defined in the payset.For example, in one embodiment, average call handle time may be definedas a metric. In this embodiment, to achieve the stretch level an agentmust have an average handle time less than 330 seconds (achievement).While to meet the target level, an agent may only need to have anaverage call time of less than 390 seconds (achievement). The awardopportunity levels are also defined in relation to an agent'scompensation. If an agent's compensation is relatively higher than otheragents, then the award opportunity defined for the agent will also berelatively lower. That is, an agent compensated at a higher level isexpected to meet higher achievement levels. If an agent achieves adifferent level for one or more of the metrics, the agents overallperformance will be ranked according to the lowest achieved level forany individual metric.

In addition to performance levels, a payset also defines base paylevels, which in one embodiment may include: learning, successful,successful+, and role model. The pay levels represent the monetary basepay for an agent. For example, in an embodiment, learning represents alower base pay relative to successful, which represents a lower base payrelative to successful+. As described above, the pay level is used todefine achievement values, and is also used in combination with theperformance level to evaluate an agent's performance. The combination ofperformance level and pay level may be embodied in a table such as Table2, described above. The paysets defined using administration application714 (the combination of pay level, performance level, and achievementvalues) are used to evaluate an agent and make adjustments to theircompensation. For example, an agent with base pay at a learning paylevel who achieves a role model performance level may be eligible for anincrease in compensation. Paysets can be defined and applied to a site,client, program, job title, and/or call type.

In one embodiment, administration application 714 may also define paysets that are designed to account for an organization's concern overprofits. As one example, in the customer service industry a client maycontract an organization which employs customer service agents to takecalls from the client's customers. In this example, the client may paythe organization a set amount of money per agent. The more an agent ispaid by the organization, the less the organization will make as profit.Accordingly, the compensation rule may be adapted to reflect this. Inone embodiment, an agent must achieve a performance level above adefined performance level, e.g. the threshold performance level, toincrease their base pay. However, when their base pay increases, theamount available for variable pay will decrease. For example, an agentmay have a base pay of $10.00/hour and the potential for receiving avariable pay amount that is 20% of their base pay. If the agent performsat a high level for a predetermined period of time, their base pay mayincrease to $11.00/hour, however their potential variable pay may bereduced to only 10% of their base pay. This type of compensation rulestill incentivizes agents, because their base pay (i.e., guaranteedmoney) is increased with better performance, but also takes intoconsideration the costs/margins of an organization. It is contemplatedthat other compensation rules may be defined to apply to varioussituations, and the present invention is not limited to any specificcompensation rule.

PO application 110 uses the paysets defined using the administrationapplication 714, and the agent's metrics calculated and provided by themetrics layer 712 to evaluate an agent's performance, determinecompensation adjustments 716, and provide access to an agent'sperformance using interfaces 116, 118, and 120. In one embodiment, thePO application 110 evaluates an agent's performance daily, including aperformance evaluation for the day and updated cumulative monthlyperformances. As described above, the performance results are accessedthrough interfaces 116, 118, and 120. Accordingly, PO application 110allows real-time monitoring of an agent's performance on a daily basis.

As shown in FIG. 8, PO application 110 calculates compensationadjustments 716 based on the defined paysets, and transmits thecompensation adjustments 716 to payroll application 718, where they areimplemented. As will be appreciated, in some embodiments thecompensation adjustments 716 may be calculated daily along with agents'performances, but only applied every pay period. Payroll application 718may be any conventional payroll application that is used to manage thepayroll of an organization.

In some embodiments, the compensation adjustments calculated by POapplication 110 are made and applied automatically, without anyadditional input by a manager. In this embodiment, an administratorwill, in addition to defining metrics and paysets, also define rules forproviding compensation adjustments 716. For example, using thepreviously discussed base pay levels and performance levels, anadministrator may establish a rule that whenever an agent performs atthe role model performance level for 5 consecutive days, the agent willautomatically receive a bonus (e.g., 2% of their base salary). In thisexample, when PO application calculates the performance levels foragents, it will automatically apply the rules established by theadministrator and provide compensation adjustments 716 accordingly topayroll application 108. In other embodiments, a manager may access POapplication 110 using interface 118 or 120 and manually applycompensation adjustments 716 based on viewing performance levels foragents. The compensation adjustments will then be provided to payrollapplication 718.

FIG. 9 illustrates a process 800 for implementing the PO business model180 for optimizing the performance of agents, and for generatingcompensation adjustments to modify compensation of agents based on theirperformance. As such, the process 800 is operable to evaluate anagent's, team's or entire organization's performance against relativecriterion, or metrics, and link such evaluation to financialconsiderations. The process 800 is described below with reference toonly one agent for simplicity purposes; however, it should beappreciated that the process is preferably practiced in numerousinstances for each agent in an organization. The process 800 isperformed using an operation flow that begins with a start operation 802and ends with a finish operation 814. The start operation 802 isinitiated to begin optimizing the performance of a specific agent in anorganization. From the start operation 802, the operation flow initiallypasses to acquire and aggregate data operation 804.

The acquire and aggregate data operation 804, collects data that isrelevant to evaluating the performance of an agent with respect to anorganization's strategic goals. The type of data that is acquired andaggregated during operation 804 will depend on the tasks that an agentis performing for the organization. For example, if the agent is acustomer service representative, then the data acquired and aggregatedduring operation 804 may relate to data such as call handling time,quality assessment, number of hours worked, and number of calls handled.However, as will be appreciated, the data may relate to any datarelevant to evaluating agents.

After the acquire and aggregate data operation 804, the operation flowpasses to calculate metrics 806. The calculate metrics operation 806uses the data collected from operation 804 to calculate agent'sperformance metrics. As described above, performance metrics may bepredefined along with threshold values. In operation 806, the dataacquired during operation 804 is used along with predefined metrics tocalculate an agent's metrics, which are then compared to the achievementvalues to evaluate the performance of an agent (operation 808 describedbelow). For example, in one embodiment a metric may be defined as theaverage time it takes an agent to handle a call. In this embodiment, thecalculate metrics operation 806 uses the data for the number of callshandled by an agent and the total call time of an agent (acquired andaggregated at operation 804) to calculate an average call time for anagent.

The agent's metrics calculated at operation 806 are used in operation808 to determine/evaluate an agent's performance level. Operation 808involves comparing the agent metrics, to established achievement values,which are predefined in relation to performance levels and acompensation (e.g., base pay) level of the agent. For example, in anembodiment, there may be four performance levels: below threshold,threshold, target and stretch. To be ranked within a performance level,an agent's metrics must meet achievement values defined for each level.In one embodiment, average call handle time may be defined as a metric.In an embodiment, to achieve the stretch level an agent must have anaverage handle time less than 330 seconds (achievement). In someembodiments, if an agent achieves a different level for one or moremetrics, the agents overall performance will be ranked according to thelowest achieved level for any individual metric.

Process flow passes to operation 810 where the performance level is usedto determine compensation adjustments. The compensation adjustments maybe determined using any method that uses the performance level fromoperation 808. In one embodiment, the performance level is analyzed incombination with a compensation (e.g., base pay level) to determine thecompensation adjustments for an agent. One implementation of thisembodiment was discussed above with respect to Table 2. As describedabove, the performance level is evaluated relative to an agent's basepay level and determinations are made whether the agent's performancelevel warrants an increase or decrease in compensation. In oneembodiment, operation 810 may involve determining whether and agent'sperformance has remained at a predetermined level for a number ofmonths. As one example, if an agent has maintained a relatively highlevel of performance for three months, (as determined by comparing theperformance level to a current base pay level) the agent may warrant anincrease in base pay. On the other hand, if an agent has maintained arelatively low level of performance for three months, (as determined bycomparing the performance level to a current base pay level) the agentmay warrant a decrease in base pay.

At operation 812, the compensation adjustments determined from operation810 are applied. In some embodiments, the compensation adjustmentsinvolve variable pay such as bonuses. In other embodiments, thecompensation adjustments may involve changes (increase or decrease) tobase pay.

Having described the embodiments and various advantages of the presentinvention with reference to the figures above, it should be appreciatedthat numerous modifications may be made to the present invention thatwill readily suggest themselves to those skilled in the art and whichare encompassed in the spirit of the invention disclosed and as definedin the appended claims. Indeed, while a presently preferred embodimenthas been described for purposes of this disclosure, various changes andmodifications may be made which are well within the scope of the presentinvention.

1. A non-transitory computer readable storage medium for storinginstructions that, when executed by a processor, cause the processor toperform a method for comparing performance of two groups of agentsemployed by an organization to perform tasks, the method comprising thesteps of: defining a first metric for a first group of agents, the firstmetric relating to a first task; defining a second metric for a secondgroup of agents, the second metric relating to a second task; defining aplurality of performance levels applicable to the first metric and thesecond metric enabling a normalized basis of comparison of the firstgroup of agents to the second group of agents; establishing a firstplurality of achievement values for the first metric, wherein each ofthe first plurality of achievement values are associated with one of theplurality of performance levels; establishing a second plurality ofachievement values for the second metric, wherein each of the secondplurality of achievement values are associated with one of the pluralityof performance levels; storing the first metric, the second metric, theplurality of performance levels, the first plurality of achievementvalues, and the second plurality of achievement values in a memorydevice accessible by the processor; monitoring a performance for thefirst group of agents with respect to the first metric to determine afirst agent performance for each agent in the first group and storing inthe memory device the first agent performance for each agent in thefirst group; monitoring a performance for the second group of agentswith respect to the second metric to determine a second agentperformance for each agent in the second group and storing in the memorydevice the second agent performance for each agent in the second group;classifying by the processor the performance for the first group ofagents by comparing on the normalized basis of comparison the firstagent performance for each agent to the first plurality of achievementvalues; classifying by the processor the performance for the secondgroup of agents by comparing on the normalized basis of comparison thesecond agent performance for each agent to the second plurality ofachievement values; and evaluating group performance on the normalizedbasis of comparison by the processor by determining how many agents inthe first group are classified within each of the plurality ofperformance levels and how many agents in the second group areclassified within each of the plurality of performance levels in orderto determine which of the first group of agents or the second group ofagents is performing at a higher or lower level relative to the othergroup of agents.
 2. The non-transitory computer readable storage mediumfor storing instructions that, when executed by a processor, cause theprocessor to perform the method of claim 1, wherein the plurality ofperformance levels comprises a first performance level and a secondperformance level, the first performance level representing a higherperformance than the second performance level.
 3. The non-transitorycomputer readable storage medium for storing instructions that, whenexecuted by a processor, cause the processor to perform the method ofclaim 1, wherein the first metric and the second metric are the same,and the first plurality of achievement values are different from thesecond plurality of achievement values.
 4. The non-transitory computerreadable storage medium for storing instructions that, when executed bya processor, cause the processor to perform the method of claim 3,wherein the first task and second task comprise answering customerservice phone calls and the first metric is average call handling time.5. The non-transitory computer readable storage medium for storinginstructions that, when executed by a processor, cause the processor toperform the method of claim 3, wherein the first task and second taskcomprise answering customer service phone calls and the first metric isfirst call resolution.
 6. The non-transitory computer readable storagemedium for storing instructions that, when executed by a processor,cause the processor to perform the method of claim 1, wherein the firstmetric is different from the second metric.
 7. The non-transitorycomputer readable storage medium for storing instructions that, whenexecuted by a processor, cause the processor to perform the method ofclaim 1, further comprising the step of: based upon the evaluating ofgroup performance on the normalized basis of comparison step, providingadditional coaching and support to the first group of agents or thesecond group of agents having the lower performing level.
 8. Thenon-transitory computer readable storage medium for storing instructionsthat, when executed by a processor, cause the processor to perform themethod of claim 1, wherein the defining a plurality of performancelevels applicable to the first metric and the second metric furthercomprises the step of: defining the performance levels as belowthreshold, threshold, target, and stretch, wherein stretch is a higherperformance level than target, target is a higher performance level thanthreshold, and threshold is a higher performance level than threshold.9. The non-transitory computer readable storage medium for storinginstructions that, when executed by a processor, cause the processor toperform the method of claim 1, wherein the monitoring and storing stepsare performed on a daily basis.
 10. The non-transitory computer readablestorage medium for storing instructions that, when executed by aprocessor, cause the processor to perform the method of claim 1, furthercomprising the step of: defining a next metric for a next group ofagents, the next metric relating to a next task; defining a plurality ofperformance levels applicable to the next metric enabling a normalizedbasis of comparison of the next group of agents to the first group ofagents and the second group of agents; establishing a next plurality ofachievement values for the next metric, wherein each of the nextplurality of achievement values are associated with one of the pluralityof performance levels; storing the next metric and the next plurality ofachievement values in the memory device accessible by the processor;monitoring a performance for the next group of agents with respect tothe next metric to determine a next agent performance for each agent inthe next group and storing in the memory device the next agentperformance for each agent in the next group; classifying by theprocessor the performance for the next group of agents by comparing onthe normalized basis of comparison the next agent performance for eachagent to the next plurality of achievement values; evaluating groupperformance on the normalized basis of comparison by the processor bydetermining how many agents in the first group are classified withineach of the plurality of performance levels and how many agents in thesecond group are classified within each of the plurality of performancelevels and how many agents in the next group are classified within eachof the plurality of performance levels in order to determine which ofthe first group of agents or the second group of agents or the nextgroup of agents is performing at a higher or lower level relative to theother group of agents.
 11. The non-transitory computer readable storagemedium for storing instructions that, when executed by a processor,cause the processor to perform the method of claim 10, furthercomprising the step of: based upon the evaluating of group performanceon the normalized basis of comparison step, providing additionalcoaching and support to the first group of agents or the second group ofagents or the next group of agents having the lower performing level.12. The non-transitory computer readable storage medium for storinginstructions that, when executed by a processor, cause the processor toperform the method of claim 10, further comprising the step of:repeating the steps in claims 10 and 11 for one or more additional nextgroup of agents.